B- and T-Lymphocyte Attenuator in Systemic Lupus Erythematosus Disease Pathogenesis

B- and T-lymphocyte attenuator (BTLA; CD272) is an immunoglobulin superfamily member and part of a family of checkpoint inhibitory receptors that negatively regulate immune cell activation. The natural ligand for BTLA is herpes virus entry mediator (HVEM; TNFRSF14), and binding of HVEM to BTLA leads to attenuation of lymphocyte activation. In this study, we evaluated the role of BTLA and HVEM expression in the pathogenesis of systemic lupus erythematosus (SLE), a multisystem autoimmune disease. Peripheral blood mononuclear cells from healthy volunteers (N = 7) were evaluated by mass cytometry by time-of-flight to establish baseline expression of BTLA and HVEM on human lymphocytes compared with patients with SLE during a self-reported flare (N = 5). High levels of BTLA protein were observed on B cells, CD4+, and CD8+ T cells, and plasmacytoid dendritic cells in healthy participants. HVEM protein levels were lower in patients with SLE compared with healthy participants, while BTLA levels were similar between SLE and healthy groups. Correlations of BTLA-HVEM hub genes' expression with patient and disease characteristics were also analyzed using whole blood gene expression data from patients with SLE (N = 1,760) and compared with healthy participants (N = 60). HVEM, being one of the SLE-associated genes, showed an exceptionally strong negative association with disease activity. Several other genes in the BTLA-HVEM signaling network were strongly (negative or positive) correlated, while BTLA had a low association with disease activity. Collectively, these data provide a clinical rationale for targeting BTLA with an agonist in SLE patients with low HVEM expression.

Group 1 metabotropic glutamate receptor expression defines a T cell memory population during chronic Toxoplasma infection that enhances IFN-gamma and perforin production in the CNS

Within the brain, a pro-inflammatory response is essential to prevent clinical disease due to Toxoplasma gondii reactivation. Infection in the immunocompromised leads to lethal Toxoplasmic encephalitis while in the immunocompetent, there is persistent low-grade inflammation which is devoid of clinical symptoms. This signifies that there is a well-balanced and regulated inflammatory response to T. gondii in the brain. T cells are the dominant immune cells that prevent clinical disease, and this is mediated through the secretion of effector molecules such as perforins and IFN-γ. The presence of cognate antigen, the expression of survival cytokines, and the alteration of the epigenetic landscape drive the development of memory T cells. However, specific extrinsic signals that promote the formation and maintenance of memory T cells within tissue are poorly understood. During chronic infection, there is an increase in extracellular glutamate that, due to its function as an excitatory neurotransmitter, is normally tightly controlled in the CNS. Here we demonstrate that CD8+ T cells from the T. gondii-infected brain parenchyma are enriched for metabotropic glutamate receptors (mGluR's). Characterization studies determined that mGluR+ expression by CD8+ T cells defines a distinct memory population at the transcriptional and protein level. Finally, using receptor antagonists and agonists we demonstrate mGluR signaling is required for optimal CD8+ T cell production of the effector cytokine IFNγ. This work suggests that glutamate is an important environmental signal of inflammation that promotes T cell function. Understanding glutamate's influence on T cells in the brain can provide insights into the mechanisms that govern protective immunity against CNS-infiltrating pathogens and neuroinflammation.

Unusual structural and functional features of TpLRR/BspA-like LRR proteins

Leucine Rich Repeat (LRR) domains, are present in hundreds of thousands of proteins across all kingdoms of life and are typically involved in protein-protein interactions and ligand recognition. LRR domains are classified into eight classes and when examined in three dimensions seven, of them form curved solenoid-like super-helices, also described as toruses, with a beta sheet on the concave (inside) and stacked alpha-helices on the convex (outside) of the torus. Here we present an overview of the least characterized 8th class of LRR proteins, the TpLRR-like LRRs, named after the Treponema pallidum protein Tp0225. Proteins from the TpLRR class differ from the proteins in all other known LRR classes by having a flipped curvature, with the beta sheet on the convex side of the torus and irregular secondary structure instead of helices on the opposite, now concave site. TpLRR proteins also present highly divergent sequence pattern of individual repeats and can associate with specific types of additional domains. Several of the characterized proteins from this class, specifically the BspA-like proteins, were found in human bacterial and protozoan pathogens, playing an important role in the interactions between the pathogens and the host immune system. In this paper we surveyed all existing experimental structures and selected AlphaFold models of the best-known proteins containing this class of LRR repeats, analyzing the relation between the pattern of conserved residues, specific structural features and functions of these proteins.

Health disparities in COVID-19: immune and vascular changes are linked to disease severity and persist in a high-risk population in Riverside County, California

BACKGROUND

Health disparities in underserved communities, such as inadequate healthcare access, impact COVID-19 disease outcomes. These disparities are evident in Hispanic populations nationwide, with disproportionately high infection and mortality rates. Furthermore, infected individuals can develop long COVID with sustained impacts on quality of life. The goal of this study was to identify immune and endothelial factors that are associated with COVID-19 outcomes in Riverside County, a high-risk and predominantly Hispanic community, and investigate the long-term impacts of COVID-19 infection.

METHODS

112 participants in Riverside County, California, were recruited according to the following criteria: healthy control (n = 23), outpatients with moderate infection (outpatient, n = 33), ICU patients with severe infection (hospitalized, n = 33), and individuals recovered from moderate infection (n = 23). Differences in outcomes between Hispanic and non-Hispanic individuals and presence/absence of co-morbidities were evaluated. Circulating immune and vascular biomarkers were measured by ELISA, multiplex analyte assays, and flow cytometry. Follow-up assessments for long COVID, lung health, and immune and vascular changes were conducted after recovery (n = 23) including paired analyses of the same participants.

RESULTS

Compared to uninfected controls, the severe infection group had a higher proportion of Hispanic individuals (n = 23, p = 0.012) than moderate infection (n = 8, p = 0.550). Disease severity was associated with changes in innate monocytes and neutrophils, lymphopenia, disrupted cytokine production (increased IL-8 and IP-10/CXCL10 but reduced IFNλ2/3 and IFNγ), and increased endothelial injury (myoglobin, VCAM-1). In the severe infection group, a machine learning model identified LCN2/NGAL, IL-6, and monocyte activation as parameters associated with fatality while anti-coagulant therapy was associated with survival. Recovery from moderate COVID infection resulted in long-term immune changes including increased monocytes/lymphocytes and decreased neutrophils and endothelial markers. This group had a lower proportion of co-morbidities (n = 8, p = 1.0) but still reported symptoms associated with long COVID despite recovered pulmonary function.

CONCLUSION

This study indicates increased severity of COVID-19 infection in Hispanic individuals of Riverside County, California. Infection resulted in immunological and vascular changes and long COVID symptoms that were sustained for up to 11 months, however, lung volume and airflow resistance was recovered. Given the immune and behavioral impacts of long COVID, the potential for increased susceptibility to infections and decreased quality of life in high-risk populations warrants further investigation.

Sexual dimorphism in obesity is governed by RELMα regulation of adipose macrophages and eosinophils

Obesity incidence is increasing worldwide with the urgent need to identify new therapeutics. Sex differences in immune cell activation drive obesity-mediated pathologies where males are more susceptible to obesity comorbidities and exacerbated inflammation. Here, we demonstrate that the macrophage-secreted protein RELMα critically protects females against high-fat diet (HFD)-induced obesity. Compared to male mice, serum RELMα levels were higher in both control and HFD-fed females and correlated with frequency of adipose macrophages and eosinophils. RELMα-deficient females gained more weight and had proinflammatory macrophage accumulation and eosinophil loss in the adipose stromal vascular fraction (SVF), while RELMα treatment or eosinophil transfer rescued this phenotype. Single-cell RNA-sequencing of the adipose SVF was performed and identified sex and RELMα-dependent changes. Genes involved in oxygen sensing and iron homeostasis, including hemoglobin and lncRNA Gm47283/Gm21887, correlated with increased obesity, while eosinophil chemotaxis and response to amyloid-beta were protective. Monocyte-to-macrophage transition was also dysregulated in RELMα-deficient animals. Collectively, these studies implicate a RELMα-macrophage-eosinophil axis in sex-specific protection against obesity and uncover new therapeutic targets for obesity.

US National Institutes of Health Prioritization of SARS-CoV-2 Variants

Since late 2020, SARS-CoV-2 variants have regularly emerged with competitive and phenotypic differences from previously circulating strains, sometimes with the potential to escape from immunity produced by prior exposure and infection. The Early Detection group is one of the constituent groups of the US National Institutes of Health National Institute of Allergy and Infectious Diseases SARS-CoV-2 Assessment of Viral Evolution program. The group uses bioinformatic methods to monitor the emergence, spread, and potential phenotypic properties of emerging and circulating strains to identify the most relevant variants for experimental groups within the program to phenotypically characterize. Since April 2021, the group has prioritized variants monthly. Prioritization successes include rapidly identifying most major variants of SARS-CoV-2 and providing experimental groups within the National Institutes of Health program easy access to regularly updated information on the recent evolution and epidemiology of SARS-CoV-2 that can be used to guide phenotypic investigations.

Gender differences in smoking-induced changes in the tumor immune microenvironment

Both gender and smoking are correlated with prevalence and outcomes in many types of cancers. Tobacco smoke is a known carcinogen through its genotoxicity but can also affect cancer progression through its effect on the immune system. In this study, we aim to evaluate the hypothesis that the effects of smoking on the tumor immune microenvironment will be influenced differently by gender using large-scale analysis of publicly available cancer datasets. We used The Cancer Genomic Atlas (TCGA) datasets (n = 2724) to analyze effects of smoking on different cancer immune subtypes and the relative abundance of immune cell types between male and female cancer patients. We further validated our results by analyzing additional datasets, including Expression Project for Oncology (expO) bulk RNA-seq dataset (n = 1118) and single-cell RNA-seq dataset (n = 14). Results of our study indicate that in female patients, two immune subtypes, C1 and C2, are respectively over and under abundant in smokers vs. never smokers. In males, the only significant difference is underabundance of the C6 subtype in smokers. We identified gender-specific differences in the population of immune cell types between smokers and never smokers in all TCGA and expO cancer types. Increased plasma cell population was identified as the most consistent feature distinguishing smokers and never smokers, especially in current female smokers based on both TCGA and expO data. Our analysis of existing single-cell RNA-seq data further revealed that smoking differentially affects the gene expression profile of cancer patients based on the immune cell type and gender. In our analysis, female and male smokers show different smoking-induced patterns of immune cells in tumor microenvironment. Besides, our results suggest cancer tissues directly exposed to tobacco smoke undergo the most significant changes, but all other cancer types are affected as well. Findings of current study also indicate that changes in the populations of plasma cells and their correlations to survival outcomes are stronger in female current smokers, with implications for cancer immunotherapy of women smokers. In conclusion, results of this study can be used to develop personalized treatment plans for cancer patients who smoke, particularly women smokers, taking into account the unique immune cell profile of their tumors.

Sexual dimorphism in obesity is governed by RELMα regulation of adipose macrophages and eosinophils

Obesity incidence is increasing worldwide with the urgent need to identify new therapeutics. Sex differences in immune cell activation drive obesity-mediated pathologies where males are more susceptible to obesity co-morbidities and exacerbated inflammation. Here, we demonstrate that the macrophage-secreted protein RELMα critically protects females against high fat diet-induced obesity. Compared to male mice, RELMα levels were elevated in both control and high fat dietfed females and correlated with adipose macrophages and eosinophils. RELMα-deficient females gained more weight and had pro-inflammatory macrophage accumulation and eosinophil loss, while both RELMα treatment and eosinophil transfer rescued this phenotype. Single cell RNA-sequencing of the adipose stromal vascular fraction was performed and identified sex and RELMα-dependent changes. Genes involved in oxygen sensing and iron homeostasis, including hemoglobin and lncRNA Gm47283, correlated with increased obesity, while eosinophil chemotaxis and response to amyloid-beta were protective. Monocyte-to-macrophage transition was also dysregulated in RELMα-deficient animals. Collectively, these studies implicate a RELMα-macrophage-eosinophil axis in sex-specific protection against obesity and uncover new therapeutic targets for obesity.

1470. Human monoclonal antibodies for the treatment and prevention of Crimean Congo Hemorrhagic Fever

Background

Crimean-Congo hemorrhagic fever (CCHF) is the most widely spread viral hemorrhagic disease, found in Europe, Asia, and Africa. The disease symptoms start and progress rapidly and can lead to bruising and bleeding, with high fatality rates of up to 50% in hospitalized patients. Currently there are no approved vaccines or therapeutics available, and treatment is supportive.

The CCHFV glycoprotein is made up of two major structural glycoproteins, GC and GN, which are required for the virus attachment and entry. An additional protein, GP38, is a secreted byproduct derived from a glycoproptein precursor of GN and whose role remains unknown. Recently, the non-neutralizing mouse mAb 13G8 (anti-GP38) has shown 60-90% protection prophylactically or post-challenge in a mouse model when challenged with various CCHFV strains. This is noteworthy because neutralizing mouse mAbs to GC have not shown consistent protection in mouse models. Because most of the work has been on mice up till now, we decided to isolate and study mAbs from human survivors of CCHF.

Methods

The antibody response to GC and GP38 were measured in CCHF patients from Turkey ∼ 6 months after infection, and one high titer sample was selected for mAb isolation. For this purpose, a combined proteomics/genomics approach was performed; plasma Abs were isolated using sequential affinity chromatography, peptides subjected to Mass spectrometry, and then matched to single cell VDJ sequence libraries constructed from PBMCs. mAbs were tested for binding and neutralization, and one candidate used for in-vivo evaluation with Ifnar1- mice (lacking IFN) challenged with CCHF virus.

Results

11 anti-GP38 and 8 anti-Gc antibodies were isolated. All anti-Gc (and none of the GP38) mAbs exhibited neutralization. Anti-GP38 antibodies were segregated into 6 epitope groups based on competition assays (including 3 not described before). CC5-17, the human mAb sharing the same epitope as 13G8, showed 50% protection two separate experiments in Ifnar1- mice (when given 30 minutes prior to challenge, or 1 and 4 days after challenge).

Conclusion

The non-neutralizing gp38 antibodies have proven to afford protection before or after exposure to CCHFV. Human mAbs have the potential for protection and/or prevention of CCHF.

Disclosures

All Authors: No reported disclosures.

ViralVar: A Web Tool for Multilevel Visualization of SARS-CoV-2 Genomes

The unprecedented growth of publicly available SARS-CoV-2 genome sequence data has increased the demand for effective and accessible SARS-CoV-2 data analysis and visualization tools. The majority of the currently available tools either require computational expertise to deploy them or limit user input to preselected subsets of SARS-CoV-2 genomes. To address these limitations, we developed ViralVar, a publicly available, point-and-click webtool that gives users the freedom to investigate and visualize user-selected subsets of SARS-CoV-2 genomes obtained from the GISAID public database. ViralVar has two primary features that enable: (1) the visualization of the spatiotemporal dynamics of SARS-CoV-2 lineages and (2) a structural/functional analysis of genomic mutations. As proof-of-principle, ViralVar was used to explore the evolution of the SARS-CoV-2 pandemic in the USA in pediatric, adult, and elderly populations (n > 1.7 million genomes). Whereas the spatiotemporal dynamics of the variants did not differ between these age groups, several USA-specific sublineages arose relative to the rest of the world. Our development and utilization of ViralVar to provide insights on the evolution of SARS-CoV-2 in the USA demonstrates the importance of developing accessible tools to facilitate and accelerate the large-scale surveillance of circulating pathogens.

Genetic Divergence of Vibrio vulnificus Clinical Isolates with Mild to Severe Outcomes

The marine bacterium Vibrio vulnificus infects humans via food or water contamination, leading to serious manifestations, including gastroenteritis, wound infections, and septic shock. Previous studies suggest phylogenetic Lineage 1 isolates with the vcgC allele of the vcg gene cause human infections, whereas Lineage 2 isolates with the vcgE allele are less pathogenic. Mouse studies suggest that some variants of the primary toxin could drive more serious infections. A collection of 109 V. vulnificus United States human clinical isolates from 2001 to 2019 with paired clinical outcome data were assembled. The isolates underwent whole-genome sequencing, multilocus-sequence phylogenetic analysis, and toxinotype analysis of the multifunctional autoprocessing repeats-in-toxin (MARTX) toxin. In contrast to prior reports, clinical isolates were equally distributed between lineages. We found no correlation between phylogenetic lineage or MARTX toxinotype and disease severity. Infections caused by isolates in Lineage 1 demonstrated a borderline statistically significant higher mortality. Lineage 1 isolates had a trend toward a higher proportion of M-type MARTX toxins compared with Lineage 2, although this was not statistically significant. IMPORTANCE Vibrio vulnificus is an aquatic pathogen that is capable of causing severe disease in humans. Previous studies have suggested that pathogenic isolates were restricted to certain phylogenetic lineages and possibly toxinotype. Our study demonstrated that phylogenetic lineage and multifunctional autoprocessing repeats-in-toxin (MARTX) toxinotype do not predict severity of infection. V. vulnificus strains capable of causing severe human disease are not concentrated in Lineage 1 but are genetically diverse. Thus, food surveillance based on lineage type or toxinotype may not be an appropriate intervention measure to control this rare but serious infection.

Resistin Concentration in Early Sepsis and All-Cause Mortality at a Safety-Net Hospital in Riverside County

Background

Sepsis mortality has remained unchanged for greater than a decade, and early recognition continues to be the most important factor in mortality outcome. Plasma resistin concentration is increased in sepsis, but its mechanism and clinical relevance is unclear. As one function, resistin interacts with toll-like receptor 4 in competition with lipopolysaccharide, a main component of the gram-negative bacterial cell wall. It is not known if the type of infection leading to sepsis influences resistin production. The objective of this study was to investigate whether 1) early plasma resistin concentration can predict mortality, 2) elevated plasma resistin concentration is associated with clinical disease severity scores, such as SOFA, mSOFA and APACHE II, and 3) plasma resistin concentrations differ between gram negative versus other etiologies of sepsis.

Methods

This was an exploratory study in the framework of a prospective observational design. Peripheral venous blood samples were obtained from subjects admitted to the intensive care unit at clinical recognition of sepsis (0 hour) and at 6 and 24 hours. Vasopressor utilization was not a requirement for inclusion. Plasma was analyzed for resistin concentration by ELISA. Cytokine concentrations including IL-6, IL-8, and IL-10 were determined by cytokine bead array. Cytokine data were evaluated against publicly available sepsis RNA expression datasets to compare protein versus RNA expression levels in predicting clinical disease state. Clinical data were collected from electronic health records for clinical severity index calculations and context for interpretation of resistin and cytokine concentrations. Subjects were followed up to 60 days, or until death, whichever came first. Statistical analysis was completed with R package and SPSS software.

Results

Resistin levels were elevated in subjects admitted to the intensive care unit with sepsis. Four-hundred subjects were screened with 45 subjects included in the final analysis. Thirteen of 45 patients were non-survivors. Mortality within 60 days correlated with significantly higher resistin concentrations than in survivors. A resistin concentration of >126 ng/mL at clinical recognition of sepsis and >197 ng/mL within the first 24 hours were associated with mortality within 60 days with an area under the curve of 0.82 and 0.88, respectively. Most subjects with resistin concentration greater than these threshold values were deceased prior to 30 days. Resistin concentrations correlated with SOFA, mSOFA, and APACHE II scores in addition to having association with increases in inflammatory and sepsis biomarkers. These associations were validated with analysis of RNA expression datasets.

Conclusion

Plasma resistin concentrations of >126 ng/mL at clinical recognition of sepsis and >197 ng/mL within the first 24 hours of clinical sepsis recognition are associated with all-cause mortality. Resistin concentration within this timeframe also has comparable mortality association to well-validated clinical severity indices of SOFA, mSOFA, and APACHE II scores.

What the protein data bank tells us about the evolutionary conservation of protein conformational diversity

Proteins sample a multitude of different conformations by undergoing small- and large-scale conformational changes that are often intrinsic to their functions. Information about these changes is often captured in the Protein Data Bank by the apparently redundant deposition of independent structural solutions of identical proteins. Here, we mine these data to examine the conservation of large-scale conformational changes between homologous proteins. This is important for both practical reasons, such as predicting alternative conformations of a protein by comparative modeling, and conceptual reasons, such as understanding the extent of conservation of different features in evolution. To study this question, we introduce a novel approach to compare conformational changes between proteins by the comparison of their difference distance maps (DDMs). We found that proteins undergoing similar conformational changes have similar DDMs and that this similarity could be quantified by the correlation between the DDMs. By comparing the DDMs of homologous protein pairs, we found that large-scale conformational changes show a high level of conservation across a broad range of sequence identities. This shows that conformational space is usually conserved between homologs, even relatively distant ones.

Increased Frequency of Indels in Hypervariable Regions of SARS-CoV-2 Proteins—A Possible Signature of Adaptive Selection

Most attention in the surveillance of evolving SARS-CoV-2 genome has been centered on nucleotide substitutions in the spike glycoprotein. We show that, as the pandemic extends into its second year, the numbers and ratio of genomes with in-frame insertions and deletions (indels) increases significantly, especially among the variants of concern (VOCs). Monitoring of the SARS-CoV-2 genome evolution shows that co-occurrence (i.e., highly correlated presence) of indels, especially deletions on spike N-terminal domain and non-structural protein 6 (NSP6) is a shared feature in several VOCs such as Alpha, Beta, Delta, and Omicron. Indels distribution is correlated with spike mutations associated with immune escape and growth in the number of genomes with indels coincides with the increasing population resistance due to vaccination and previous infections. Indels occur most frequently in the spike, but also in other proteins, especially those involved in interactions with the host immune system. We also showed that indels concentrate in regions of individual SARS-CoV-2 proteins known as hypervariable regions (HVRs) that are mostly located in specific loop regions. Structural analysis suggests that indels remodel viral proteins’ surfaces at common epitopes and interaction interfaces, affecting the virus’ interactions with host proteins. We hypothesize that the increased frequency of indels, the non-random distribution of them and their independent co-occurrence in several VOCs is another mechanism of response to elevated global population immunity.

Dynamic changes in human single-cell transcriptional signatures during fatal sepsis

Systemic infections, especially in patients with chronic diseases, may result in sepsis: an explosive immune response that can lead to multisystem organ failure with a high mortality rate. Patients with similar clinical phenotypes or sepsis biomarker expression upon diagnosis may have different outcomes, suggesting that the dynamics of sepsis is critical in disease progression. A within-subject study of patients with Gram-negative bacterial sepsis with surviving and fatal outcomes was designed and single-cell transcriptomic analyses of peripheral blood mononuclear cells (PBMC) collected during the critical period between sepsis diagnosis and 6 h were performed. The single-cell observations in the study are consistent with trends from public datasets but also identify dynamic effects in individual cell subsets that change within hours. It is shown that platelet and erythroid precursor responses are drivers of fatal sepsis, with transcriptional signatures that are shared with severe COVID-19 disease. It is also shown that hypoxic stress is a driving factor in immune and metabolic dysfunction of monocytes and erythroid precursors. Last, the data support CD52 as a prognostic biomarker and therapeutic target for sepsis as its expression dynamically increases in lymphocytes and correlates with improved sepsis outcomes. In conclusion, this study describes the first single-cell study that analyzed short-term temporal changes in the immune cell populations and their characteristics in surviving or fatal sepsis. Tracking temporal expression changes in specific cell types could lead to more accurate predictions of sepsis outcomes and identify molecular biomarkers and pathways that could be therapeutically controlled.

This research was supported by the UCR School of Medicine (to A.G. and M.G.N.), the Dean Innovation Fund (to J.B. and M.G.N.), and the National Institutes of Health (NIAID, R21AI37830, and R01AI153195 to M.G.N.). The data from this study were generated at the UC San Diego IGM Genomics Center utilizing an Illumina NovaSeq 6000 that was purchased with funding from a National Institutes of Health SIG grant (#S10 OD026929).

Defining the risk of SARS-CoV-2 variants on immune protection

The global emergence of many severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants jeopardizes the protective antiviral immunity induced after infection or vaccination. To address the public health threat caused by the increasing SARS-CoV-2 genomic diversity, the National Institute of Allergy and Infectious Diseases within the National Institutes of Health established the SARS-CoV-2 Assessment of Viral Evolution (SAVE) programme. This effort was designed to provide a real-time risk assessment of SARS-CoV-2 variants that could potentially affect the transmission, virulence, and resistance to infection- and vaccine-induced immunity. The SAVE programme is a critical data-generating component of the US Government SARS-CoV-2 Interagency Group to assess implications of SARS-CoV-2 variants on diagnostics, vaccines and therapeutics, and for communicating public health risk. Here we describe the coordinated approach used to identify and curate data about emerging variants, their impact on immunity and effects on vaccine protection using animal models. We report the development of reagents, methodologies, models and notable findings facilitated by this collaborative approach and identify future challenges. This programme is a template for the response to rapidly evolving pathogens with pandemic potential by monitoring viral evolution in the human population to identify variants that could reduce the effectiveness of countermeasures.

Novel putative polyethylene terephthalate (PET) plastic degrading enzymes from the environmental metagenome

Several plastic degrading enzymes have been described in the literature, most notably PETases that are capable of hydrolyzing polyethylene terephthalate (PET) plastic. One of them, the PETase from Ideonella sakaiensis, a bacterium isolated from environmental samples within a PET bottle recycling site, was a subject of extensive studies. To test how widespread PETase functionality is in other bacterial communities, we used a cascade of BLAST searches in the JGI metagenomic datasets and showed that close homologs of I. sakaiensis PETase can also be found in other metagenomic environmental samples from both human-affected and relatively pristine sites. To confirm their classification as putative PETases, we verified that the newly identified proteins have the PETase sequence signatures common to known PETases and that phylogenetic analyses group them with the experimentally characterized PETases. Additionally, docking analysis was performed in order to further confirm the functional assignment of the putative environmental PETases.

Dynamic changes in human single-cell transcriptional signatures during fatal sepsis

Systemic infections, especially in patients with chronic diseases, may result in sepsis: an explosive, uncoordinated immune response that can lead to multisystem organ failure with a high mortality rate. Patients with similar clinical phenotypes or sepsis biomarker expression upon diagnosis may have different outcomes, suggesting that the dynamics of sepsis is critical in disease progression. A within-subject study of patients with Gram-negative bacterial sepsis with surviving and fatal outcomes was designed and single-cell transcriptomic analyses of peripheral blood mononuclear cells (PBMC) collected during the critical period between sepsis diagnosis and 6 h were performed. The single-cell observations in the study are consistent with trends from public datasets but also identify dynamic effects in individual cell subsets that change within hours. It is shown that platelet and erythroid precursor responses are drivers of fatal sepsis, with transcriptional signatures that are shared with severe COVID-19 disease. It is also shown that hypoxic stress is a driving factor in immune and metabolic dysfunction of monocytes and erythroid precursors. Last, the data support CD52 as a prognostic biomarker and therapeutic target for sepsis as its expression dynamically increases in lymphocytes and correlates with improved sepsis outcomes. In conclusion, this study describes the first single-cell study that analyzed short-term temporal changes in the immune cell populations and their characteristics in surviving or fatal sepsis. Tracking temporal expression changes in specific cell types could lead to more accurate predictions of sepsis outcomes and identify molecular biomarkers and pathways that could be therapeutically controlled to improve the sepsis trajectory toward better outcomes.

Coincident rapid expansion of two SARS-CoV-2 lineages with enhanced infectivity in Nigeria

The emergence of new SARS-CoV-2 variants with enhanced transmissibility or decreased susceptibility to immune responses is a major threat to global efforts to end the coronavirus disease 2019 (COVID-19) pandemic. Disparities in viral genomic surveillance capabilities and efforts have resulted in gaps in our understanding of the viral population dynamics across the globe. Nigeria, despite having the largest population of any nation in Africa, has had relatively little SARS-CoV-2 sequence data made publicly available. Here we report the whole-genome sequences of 74 SARS-CoV-2 isolates collected from individuals in Oyo State, Nigeria in January 2021. Most isolates belonged to either the B.1.1.7 Alpha "variant of concern" or the B.1.525 Eta lineage, which is currently considered a "variant of interest" containing multiple spike protein mutations previously associated with enhanced transmissibility and possible immune escape. Nigeria has the highest reported frequency of the B.1.525 lineage globally with phylogenetic characteristics consistent with a recent monophyletic origin and rapid expansion. Spike protein from the B.1.525 lineage displayed both increased infectivity and decreased neutralization by convalescent sera compared to Spike proteins from other clades. These results, along with indications that the virus is outpacing the B.1.1.7 lineage in Nigeria, suggest that the B.1.525 lineage represents another "variant of concern" and further underline the importance of genomic surveillance in undersampled regions across the globe.

The interplay of SARS-CoV-2 evolution and constraints imposed by the structure and functionality of its proteins

The unprecedented pace of the sequencing of the SARS-CoV-2 virus genomes provides us with unique information about the genetic changes in a single pathogen during ongoing pandemic. By the analysis of close to 200,000 genomes we show that the patterns of the SARS-CoV-2 virus mutations along its genome are closely correlated with the structural and functional features of the encoded proteins. Requirements of foldability of proteins' 3D structures and the conservation of their key functional regions, such as protein-protein interaction interfaces, are the dominant factors driving evolutionary selection in protein-coding genes. At the same time, avoidance of the host immunity leads to the abundance of mutations in other regions, resulting in high variability of the missense mutation rate along the genome. "Unexplained" peaks and valleys in the mutation rate provide hints on function for yet uncharacterized genomic regions and specific protein structural and functional features they code for. Some of these observations have immediate practical implications for the selection of target regions for PCR-based COVID-19 tests and for evaluating the risk of mutations in epitopes targeted by specific antibodies and vaccine design strategies.

Large scale analysis of smoking-induced changes in the tumor immune microenvironment

Here, we expanded the recent knowledge on the immune landscape of cancer by performing a comparative analysis of tobacco smoking-induced changes in the populations of major immune cell types between smokers and never-smokers (people who have never smoked). To investigate the immune response of smokers and never-smokers, the relative abundance of immune cell types was calculated by both CIBERSORT and xCell based on TCGA RNA-seq data. We further validated the findings using publicly available bulk RNA-seq and single-cell RNA-seq data from cohorts of cancer patients other than TCGA cohort. We showed statistically significant smoking-induced changes in immune cell populations in all studied cancers. The increase in plasma cell populations and the changes in the ratio of activated to resting immune cell types were the most consistent features distinguishing smokers and never-smokers across different cancers, with both being correlated with survival outcomes. We found that the tobacco-induced changes in populations of immune cells were not as marked in cancers of tissues that are not directly exposed to smoke as in lung cancers and head and neck cancer (LUAD, LUSC, and HNSC). However, the significant differences in survival in several cancer types suggest that even a small shift in the frequency of immune cell types might result in adverse outcomes. We also showed that smoking-induced changes in the patterns of immune cell populations and their correlations to survival outcomes are stronger in female smokers than in males. In general, the findings of this study suggest that certain immune cell types could potentially be used as common prognostic markers and therapeutic targets for active smoker patients.

Identification and phylogenetic analysis of RNA binding domain abundant in apicomplexans or RAP proteins

The RNA binding domain abundant in apicomplexans (RAP) is a protein domain identified in a diverse group of proteins, called RAP proteins, many of which have been shown to be involved in RNA binding. To understand the expansion and potential function of the RAP proteins, we conducted a hidden Markov model based screen among the proteomes of 54 eukaryotes, 17 bacteria and 12 archaea. We demonstrated that the domain is present in closely and distantly related organisms with particular expansions in Alveolata and Chlorophyta, and are not unique to Apicomplexa as previously believed. All RAP proteins identified can be decomposed into two parts. In the N-terminal region, the presence of variable helical repeats seems to participate in the specific targeting of diverse RNAs, while the RAP domain is mostly identified in the C-terminal region and is highly conserved across the different phylogenetic groups studied. Several conserved residues defining the signature motif could be crucial to ensure the function(s) of the RAP proteins. Modelling of RAP domains in apicomplexan parasites confirmed an ⍺/β structure of a restriction endonuclease-like fold. The phylogenetic trees generated from multiple alignment of RAP domains and full-length proteins from various distantly related eukaryotes indicated a complex evolutionary history of this family. We further discuss these results to assess the potential function of this protein family in apicomplexan parasites.

ModFlex: Towards Function Focused Protein Modeling

There is a wide, and continuously widening, gap between the number of proteins known only by their amino acid sequence versus those structurally characterized by direct experiment. To close this gap, we mostly rely on homology-based inference and modeling to reason about the structures of the uncharacterized proteins by using structures of homologous proteins as templates. With the rapidly growing size of the Protein Data Bank, there are often multiple choices of templates, including multiple sets of coordinates from the same protein. The substantial conformational differences observed between different experimental structures of the same protein often reflect function related structural flexibility. Thus, depending on the questions being asked, using distant homologs, or coordinate sets with lower resolution but solved in the appropriate functional form, as templates may be more informative. The ModFlex server (https://modflex.org/) addresses this seldom mentioned gap in the standard homology modeling approach by providing the user with an interface with multiple options and tools to select the most relevant template and explore the range of structural diversity in the available templates. ModFlex is closely integrated with a range of other programs and servers developed in our group for the analysis and visualization of protein structural flexibility and divergence.

Understanding oncogenicity of cancer driver genes and mutations in the cancer genomics era

One of the key challenges of cancer biology is to catalogue and understand the somatic genomic alterations leading to cancer. Although alternative definitions and search methods have been developed to identify cancer driver genes and mutations, analyses of thousands of cancer genomes return a remarkably similar catalogue of around 300 genes that are mutated in at least one cancer type. Yet, many features of these genes and their role in cancer remain unclear, first and foremost when a somatic mutation is truly oncogenic. In this review, we first summarize some of the recent efforts in completing the catalogue of cancer driver genes. Then, we give an overview of different aspects that influence the oncogenicity of somatic mutations in the core cancer driver genes, including their interactions with the germline genome, other cancer driver mutations, the immune system, or their potential role in healthy tissues. In the coming years, this research holds promise to illuminate how, when, and why cancer driver genes and mutations are really drivers, and thereby move personalized cancer medicine and targeted therapies forward.

Microbial function and genital inflammation in young South African women at high risk of HIV infection

BACKGROUND

Female genital tract (FGT) inflammation is an important risk factor for HIV acquisition. The FGT microbiome is closely associated with inflammatory profile; however, the relative importance of microbial activities has not been established. Since proteins are key elements representing actual microbial functions, this study utilized metaproteomics to evaluate the relationship between FGT microbial function and inflammation in 113 young and adolescent South African women at high risk of HIV infection. Women were grouped as having low, medium, or high FGT inflammation by K-means clustering according to pro-inflammatory cytokine concentrations.

RESULTS

A total of 3186 microbial and human proteins were identified in lateral vaginal wall swabs using liquid chromatography-tandem mass spectrometry, while 94 microbial taxa were included in the taxonomic analysis. Both metaproteomics and 16S rRNA gene sequencing analyses showed increased non-optimal bacteria and decreased lactobacilli in women with FGT inflammatory profiles. However, differences in the predicted relative abundance of most bacteria were observed between 16S rRNA gene sequencing and metaproteomics analyses. Bacterial protein functional annotations (gene ontology) predicted inflammatory cytokine profiles more accurately than bacterial relative abundance determined by 16S rRNA gene sequence analysis, as well as functional predictions based on 16S rRNA gene sequence data (p < 0.0001). The majority of microbial biological processes were underrepresented in women with high inflammation compared to those with low inflammation, including a Lactobacillus-associated signature of reduced cell wall organization and peptidoglycan biosynthesis. This signature remained associated with high FGT inflammation in a subset of 74 women 9 weeks later, was upheld after adjusting for Lactobacillus relative abundance, and was associated with in vitro inflammatory cytokine responses to Lactobacillus isolates from the same women. Reduced cell wall organization and peptidoglycan biosynthesis were also associated with high FGT inflammation in an independent sample of ten women.

CONCLUSIONS

Both the presence of specific microbial taxa in the FGT and their properties and activities are critical determinants of FGT inflammation. Our findings support those of previous studies suggesting that peptidoglycan is directly immunosuppressive, and identify a possible avenue for biotherapeutic development to reduce inflammation in the FGT. To facilitate further investigations of microbial activities, we have developed the FGT-DB application that is available at http://fgtdb.org/ . Video Abstract.

Protein structure, amino acid composition and sequence determine proteome vulnerability to oxidation-induced damage

Oxidative stress alters cell viability, from microorganism irradiation sensitivity to human aging and neurodegeneration. Deleterious effects of protein carbonylation by reactive oxygen species (ROS) make understanding molecular properties determining ROS susceptibility essential. The radiation‐resistant bacterium Deinococcus radiodurans accumulates less carbonylation than sensitive organisms, making it a key model for deciphering properties governing oxidative stress resistance. We integrated shotgun redox proteomics, structural systems biology, and machine learning to resolve properties determining protein damage by γ‐irradiation in Escherichia coli and D. radiodurans at multiple scales. Local accessibility, charge, and lysine enrichment accurately predict ROS susceptibility. Lysine, methionine, and cysteine usage also contribute to ROS resistance of the D. radiodurans proteome. Our model predicts proteome maintenance machinery, and proteins protecting against ROS are more resistant in D. radiodurans. Our findings substantiate that protein‐intrinsic protection impacts oxidative stress resistance, identifying causal molecular properties.

Coronavirus3D: 3D structural visualization of COVID-19 genomic divergence

Motivation

As the COVID-19 pandemic is spreading around the world, the SARS-CoV-2 virus is evolving with mutations that potentially change and fine-tune functions of the proteins coded in its genome.

Results

Coronavirus3D website integrates data on the SARS-CoV-2 virus mutations with information about 3D structures of its proteins, allowing users to visually analyze the mutations in their 3D context.

Availability and implementation

Coronavirus3D server is freely available at https://coronavirus3d.org.

FATCAT 2.0: towards a better understanding of the structural diversity of proteins

FATCAT 2.0 server (http://fatcat.godziklab.org/), provides access to a flexible protein structure alignment algorithm developed in our group. In such an alignment, rotations and translations between elements in the structure are allowed to minimize the overall root mean square deviation (RMSD) between the compared structures. This allows to effectively compare protein structures even if they underwent structural rearrangements in different functional forms, different crystallization conditions or as a result of mutations. The major update for the server introduces a new graphical interface, much faster database searches and several new options for visualization of the structural differences between proteins

The interplay of SARS-CoV-2 evolution and constraints imposed by the structure and functionality of its proteins

Fast evolution of the SARS-CoV-2 virus provides us with unique information about the patterns of genetic changes in a single pathogen in the timescale of months. This data is used extensively to track the phylodynamic of the pandemic's spread and its split into distinct clades. Here we show that the patterns of SARS-CoV-2 virus mutations along its genome are closely correlated with the structural features of the coded proteins. We show that the foldability of proteins' 3D structures and conservation of their functions are the universal factors driving evolutionary selection in protein-coding genes. Insights from the analysis of mutation distribution in the context of the SARS-CoV-2 proteins' structures and functions have practical implications including evaluating potential antigen epitopes or selection of primers for PCR-based COVID-19 tests.

Cancer3D 2.0: interactive analysis of 3D patterns of cancer mutations in cancer subsets

Our knowledge of cancer genomics exploded in last several years, providing us with detailed knowledge of genetic alterations in almost all cancer types. Analysis of this data gave us new insights into molecular aspects of cancer, most important being the amazing diversity of molecular abnormalities in individual cancers. The most important question in cancer research today is how to classify this diversity to identify subtypes that are most relevant for treatment and outcome prediction for individual patients. The Cancer3D database at http://www.cancer3d.org gives an open and user-friendly way to analyze cancer missense mutations in the context of structures of proteins they are found in and in relation to patients’ clinical data. This approach allows users to find novel candidate driver regions for specific subgroups, that often cannot be found when similar analyses are done on the whole gene level and for large, diverse cohorts. Interactive interface allows user to visualize the distribution of mutations in subgroups defined by cancer type and stage, gender and age brackets, patient's ethnicity or vice versa find dominant cancer type, gender or age groups for specific three-dimensional mutation patterns.

Comparison of metal-bound and unbound structures of aminopeptidase B proteins from Escherichia coli and Yersinia pestis

Protein degradation by aminopeptidases is involved in bacterial responses to stress. Escherichia coli produces two metal-dependent M17 family leucine aminopeptidases (LAPs), aminopeptidase A (PepA) and aminopeptidase B (PepB). Several structures have been solved for PepA as well as other bacterial M17 peptidases. Herein, we report the first structures of a PepB M17 peptidase. The E. coli PepB protein structure was determined at a resolution of 2.05 and 2.6 Å. One structure has both Zn²⁺ and Mn²⁺ , while the second structure has two Zn²⁺ ions bound to the active site. A 2.75 Å apo structure is also reported for PepB from Yersinia pestis. Both proteins form homohexamers, similar to the overall arrangement of PepA and other M17 peptidases. However, the divergent N-terminal domain in PepB is much larger resulting in a tertiary structure that is more expanded. Modeling of a dipeptide substrate into the C-terminal LAP domain reveals contacts that account for PepB to uniquely cleave after aspartate.

Crystal structure of Nsp15 endoribonuclease NendoU from SARS-CoV-2

Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) is rapidly spreading around the world. There is no existing vaccine or proven drug to prevent infections and stop virus proliferation. Although this virus is similar to human and animal SARS-CoVs and Middle East Respiratory Syndrome coronavirus (MERS-CoVs), the detailed information about SARS-CoV-2 proteins structures and functions is urgently needed to rapidly develop effective vaccines, antibodies, and antivirals. We applied high-throughput protein production and structure determination pipeline at the Center for Structural Genomics of Infectious Diseases to produce SARS-CoV-2 proteins and structures. Here we report two high-resolution crystal structures of endoribonuclease Nsp15/NendoU. We compare these structures with previously reported homologs from SARS and MERS coronaviruses.

The crystal structure of nsp10-nsp16 heterodimer from SARS-CoV-2 in complex with S-adenosylmethionine

SARS-CoV-2 is a member of the coronaviridae family and is the etiological agent of the respiratory Coronavirus Disease 2019. The virus has spread rapidly around the world resulting in over two million cases and nearly 150,000 deaths as of April 17, 2020. Since no treatments or vaccines are available to treat COVID-19 and SARS-CoV-2, respiratory complications derived from the infections have overwhelmed healthcare systems around the world. This virus is related to SARS-CoV-1, the virus that caused the 2002-2004 outbreak of Severe Acute Respiratory Syndrome. In January 2020, the Center for Structural Genomics of Infectious Diseases implemented a structural genomics pipeline to solve the structures of proteins essential for coronavirus replication-transcription. Here we show the first structure of the SARS-CoV-2 nsp10-nsp16 2'-O-methyltransferase complex with S-adenosylmethionine at a resolution of 1.80 Å. This heterodimer complex is essential for capping viral mRNA transcripts for efficient translation and to evade immune surveillance.

Difference contact maps: From what to why in the analysis of the conformational flexibility of proteins

Protein structures, usually visualized in various highly idealized forms focusing on the three-dimensional arrangements of secondary structure elements, can also be described as lists of interacting residues or atoms and visualized as two-dimensional distance or contact maps. We show that contact maps provide an ideal tool to describe and analyze differences between structures of proteins in different conformations. Expanding functionality of the PDBFlex server and database developed previously in our group, we describe how analysis of difference contact maps (DCMs) can be used to identify critical interactions stabilizing alternative protein conformations, recognize residues and positions controlling protein functions and build hypotheses as to molecular mechanisms of disease mutations.

Structure of galactarate dehydratase, a new fold in an enolase involved in bacterial fitness after antibiotic treatment

Galactarate dehydratase (GarD) is the first enzyme in the galactarate/glucarate pathway and catalyzes the dehydration of galactarate to 3-keto-5-dehydroxygalactarate. This protein is known to increase colonization fitness of intestinal pathogens in antibiotic-treated mice and to promote bacterial survival during stress. The galactarate/glucarate pathway is widespread in bacteria, but not in humans, and thus could be a target to develop new inhibitors for use in combination therapy to combat antibiotic resistance. The structure of almost all the enzymes of the galactarate/glucarate pathway were solved previously, except for GarD, for which only the structure of the N-terminal domain was determined previously. Herein, we report the first crystal structure of full-length GarD solved using a seleno-methoionine derivative revealing a new protein fold. The protein consists of three domains, each presenting a novel twist as compared to their distant homologs. GarD in the crystal structure forms dimers and each monomer consists of three domains. The N-terminal domain is comprised of a β-clip fold, connected to the second domain by a long unstructured linker. The second domain serves as a dimerization interface between two monomers. The C-terminal domain forms an unusual variant of a Rossmann fold with a crossover and is built around a seven-stranded parallel β-sheet supported by nine α-helices. A metal binding site in the C-terminal domain is occupied by Ca2+ . The activity of GarD was corroborated by the production of 5-keto-4-deoxy-D-glucarate under reducing conditions and in the presence of iron. Thus, GarD is an unusual enolase with a novel protein fold never previously seen in this class of enzymes.

Structures of single-layer β-sheet proteins evolved from β-hairpin repeats

Free-standing single-layer β-sheets are extremely rare in naturally occurring proteins, even though β-sheet motifs are ubiquitous. Here we report the crystal structures of three homologous, single-layer, anti-parallel β-sheet proteins, comprised of three or four twisted β-hairpin repeats. The structures reveal that, in addition to the hydrogen bond network characteristic of β-sheets, additional hydrophobic interactions mediated by small clusters of residues adjacent to the turns likely play a significant role in the structural stability and compensate for the lack of a compact hydrophobic core. These structures enabled identification of a family of secreted proteins that are broadly distributed in bacteria from the human gut microbiome and are putatively involved in the metabolism of complex carbohydrates. A conserved surface patch, rich in solvent-exposed tyrosine residues, was identified on the concave surface of the β-sheet. These new modular single-layer β-sheet proteins may serve as a new model system for studying folding and design of β-rich proteins.

Comprehensive Characterization of Cancer Driver Genes and Mutations

Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%-85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors.

Golden, Jaime Pascual, Dong Xu, Anton Cheltsov, Adam Godzik

The above article from the Proteins: Structure, Function, and Bioinformatics, published online on 1 September 2014 in Wiley Online Library as Accepted Article (http://onlinelibrary.wiley.com/doi/10.1002/prot.24679/full), has been retracted by agreement between William C. Hwang, James W. Golden, Jaime Pascual, Dong Xu, Anton Cheltsov, Adam Godzik, the Editor‐in‐Chief, Bertrand E. Garcia‐Moreno, and Wiley Periodicals, Inc. The retraction has been agreed because submission was made without agreement from co‐author Adam Godzik.

Mapping genetic variations to three-dimensional protein structures to enhance variant interpretation: a proposed framework

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods.

Revealing aperiodic aspects of solenoid proteins from sequence information

MOTIVATION

Repeat proteins, which contain multiple repeats of short sequence motifs, form a large but seldom-studied group of proteins. Methods focusing on the analysis of 3D structures of such proteins identified many subtle effects in length distribution of individual motifs that are important for their functions. However, similar analysis was yet not applied to the vast majority of repeat proteins with unknown 3D structures, mostly because of the extreme diversity of the underlying motifs and the resulting difficulty to detect those.

RESULTS

We developed FAIT, a sequence-based algorithm for the precise assignment of individual repeats in repeat proteins and introduced a framework to classify and compare aperiodicity patterns for large protein families. FAIT extracts repeat positions by post-processing FFAS alignment matrices with image processing methods. On examples of proteins with Leucine Rich Repeat (LRR) domains and other solenoids like proteins, we show that the automated analysis with FAIT correctly identifies exact lengths of individual repeats based entirely on sequence information.

AVAILABILITY AND IMPLEMENTATION

https://github.com/GodzikLab/FAIT CONTACT: adam@godziklab.org

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Mutation Drivers of Immunological Responses to Cancer

In cancer immunology, somatic missense mutations have been mostly studied with regard to their role in the generation of neoantigens. However, growing evidence suggests that mutations in certain genes, such as CASP8 or TP53, influence the immune response against a tumor by other mechanisms. Identifying these genes and mechanisms is important because, just as the identification of cancer driver genes led to the development of personalized cancer therapies, a comprehensive catalog of such cancer immunity drivers will aid in the development of therapies aimed at restoring antitumor immunity. Here, we present an algorithm, domainXplorer, that can be used to identify potential cancer immunity drivers. To demonstrate its potential, we used it to analyze a dataset of 5,164 tumor samples from The Cancer Genome Atlas (TCGA) and to identify protein domains in which mutation status correlates with the presence of immune cells in cancer tissue (immune infiltrate). We identified 122 such protein regions, including several that belong to proteins with known roles in immune response, such as C2, CD163L1, or FCγR2A. In several cases, we show that mutations within the same protein can be associated with more or less immune cell infiltration, depending on the specific domain mutated. These results expand the catalog of potential cancer immunity drivers and highlight the importance of taking into account the structural context of somatic mutations when analyzing their potential association with immune phenotypes. Cancer Immunol Res; 4(9); 789-98. ©2016 AACR.

NMR in structural genomics to increase structural coverage of the protein universe: Delivered by Prof. Kurt Wüthrich on 7 July 2013 at the 38th FEBS Congress in St. Petersburg, Russia

For more than a decade, the Joint Center for Structural Genomics (JCSG; www.jcsg.org) worked toward increased three-dimensional structure coverage of the protein universe. This coordinated quest was one of the main goals of the four high-throughput (HT) structure determination centers of the Protein Structure Initiative (PSI; www.nigms.nih.gov/Research/specificareas/PSI). To achieve the goals of the PSI, the JCSG made use of the complementarity of structure determination by X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy to increase and diversify the range of targets entering the HT structure determination pipeline. The overall strategy, for both techniques, was to determine atomic resolution structures for representatives of large protein families, as defined by the Pfam database, which had no structural coverage and could make significant contributions to biological and biomedical research. Furthermore, the experimental structures could be leveraged by homology modeling to further expand the structural coverage of the protein universe and increase biological insights. Here, we describe what could be achieved by this structural genomics approach, using as an illustration the contributions from 20 NMR structure determinations out of a total of 98 JCSG NMR structures, which were selected because they are the first three-dimensional structure representations of the respective Pfam protein families. The information from this small sample is representative for the overall results from crystal and NMR structure determination in the JCSG. There are five new folds, which were classified as domains of unknown functions (DUF), three of the proteins could be functionally annotated based on three-dimensional structure similarity with previously characterized proteins, and 12 proteins showed only limited similarity with previous deposits in the Protein Data Bank (PDB) and were classified as DUFs.

A Distinct Type of Pilus from the Human Microbiome

Pili are proteinaceous polymers of linked pilins that protrude from the cell surface of many bacteria and often mediate adherence and virulence. We investigated a set of 20 Bacteroidia pilins from the human microbiome whose structures and mechanism of assembly were unknown. Crystal structures and biochemical data revealed a diverse protein superfamily with a common Greek-key β sandwich fold with two transthyretin-like repeats that polymerize into a pilus through a strand-exchange mechanism. The assembly mechanism of the central, structural pilins involves proteinase-assisted removal of their N-terminal β strand, creating an extended hydrophobic groove that binds the C-terminal donor strands of the incoming pilin. Accessory pilins at the tip and base have unique structural features specific to their location, allowing initiation or termination of the assembly. The Bacteroidia pilus, therefore, has a biogenesis mechanism that is distinct from other known pili and likely represents a different type of bacterial pilus.

UHM-ULM interactions in the RBM39-U2AF65 splicing-factor complex

RNA-binding protein 39 (RBM39) is a splicing factor and a transcriptional co-activator of estrogen receptors and Jun/AP-1, and its function has been associated with malignant progression in a number of cancers. The C-terminal RRM domain of RBM39 belongs to the U2AF homology motif family (UHM), which mediate protein-protein interactions through a short tryptophan-containing peptide known as the UHM-ligand motif (ULM). Here, crystal and solution NMR structures of the RBM39-UHM domain, and the crystal structure of its complex with U2AF65-ULM, are reported. The RBM39-U2AF65 interaction was confirmed by co-immunoprecipitation from human cell extracts, by isothermal titration calorimetry and by NMR chemical shift perturbation experiments with the purified proteins. When compared with related complexes, such as U2AF35-U2AF65 and RBM39-SF3b155, the RBM39-UHM-U2AF65-ULM complex reveals both common and discriminating recognition elements in the UHM-ULM binding interface, providing a rationale for the known specificity of UHM-ULM interactions. This study therefore establishes a structural basis for specific UHM-ULM interactions by splicing factors such as U2AF35, U2AF65, RBM39 and SF3b155, and a platform for continued studies of intermolecular interactions governing disease-related alternative splicing in eukaryotic cells.

Crystal Structure and Activity Studies of the C11 Cysteine Peptidase from Parabacteroides merdae in the Human Gut Microbiome

Clan CD cysteine peptidases, a structurally related group of peptidases that include mammalian caspases, exhibit a wide range of important functions, along with a variety of specificities and activation mechanisms. However, for the clostripain family (denoted C11), little is currently known. Here, we describe the first crystal structure of a C11 protein from the human gut bacterium, Parabacteroides merdae (PmC11), determined to 1.7-Å resolution. PmC11 is a monomeric cysteine peptidase that comprises an extended caspase-like α/β/α sandwich and an unusual C-terminal domain. It shares core structural elements with clan CD cysteine peptidases but otherwise structurally differs from the other families in the clan. These studies also revealed a well ordered break in the polypeptide chain at Lys¹⁴⁷, resulting in a large conformational rearrangement close to the active site. Biochemical and kinetic analysis revealed Lys¹⁴⁷ to be an intramolecular processing site at which cleavage is required for full activation of the enzyme, suggesting an autoinhibitory mechanism for self-preservation. PmC11 has an acidic binding pocket and a preference for basic substrates, and accepts substrates with Arg and Lys in P1 and does not require Ca²⁺ for activity. Collectively, these data provide insights into the mechanism and activity of PmC11 and a detailed framework for studies on C11 peptidases from other phylogenetic kingdoms.

PROPER: Performance visualization for optimizing and comparing ranking classifiers in MATLAB

Background

One of the recent challenges of computational biology is development of new algorithms, tools and software to facilitate predictive modeling of big data generated by high-throughput technologies in biomedical research.

Results

To meet these demands we developed PROPER - a package for visual evaluation of ranking classifiers for biological big data mining studies in the MATLAB environment.

Conclusion

PROPER is an efficient tool for optimization and comparison of ranking classifiers, providing over 20 different two- and three-dimensional performance curves.

Electronic supplementary material

The online version of this article (doi:10.1186/s13029-015-0047-1) contains supplementary material, which is available to authorized users.

PDBFlex: exploring flexibility in protein structures

The PDBFlex database, available freely and with no login requirements at http://pdbflex.org, provides information on flexibility of protein structures as revealed by the analysis of variations between depositions of different structural models of the same protein in the Protein Data Bank (PDB). PDBFlex collects information on all instances of such depositions, identifying them by a 95% sequence identity threshold, performs analysis of their structural differences and clusters them according to their structural similarities for easy analysis. The PDBFlex contains tools and viewers enabling in-depth examination of structural variability including: 2D-scaling visualization of RMSD distances between structures of the same protein, graphs of average local RMSD in the aligned structures of protein chains, graphical presentation of differences in secondary structure and observed structural disorder (unresolved residues), difference distance maps between all sets of coordinates and 3D views of individual structures and simulated transitions between different conformations, the latter displayed using JSMol visualization software.